Specifications Compared
| Spec | RTX-4070 | RTX-4080 |
|---|---|---|
| TDP | 200W | 320W |
| VRAM | 12 GB | 16 GB |
| CUDA Cores | 5,888 | 9,728 |
| Memory Type | GDDR6X | GDDR6X |
| Architecture | Ada Lovelace | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 184 | 304 |
| FP16 Performance | 29.1 TFLOPS | 48.7 TFLOPS |
| FP32 Performance | 29.1 TFLOPS | 48.7 TFLOPS |
| INT8 Performance | 466 TOPS | 780 TOPS |
| Memory Bandwidth | 504 GB/s | 717 GB/s |
Performance Analysis
The RTX 4080 SUPER demonstrates superior compute power: 48.7 TFLOPS in FP16 and FP32 compared to the RTX 4070 SUPER's 29.1 TFLOPS, a 67 percent increase. This delta accelerates deep learning training and inference, as half-precision FP16 is standard for modern neural networks, reducing training times proportionally.
Memory bandwidth marks a key differentiator: 717 GB/s on the RTX 4080 SUPER versus 504 GB/s on the RTX 4070 SUPER enables larger batch sizes in training, minimizing data transfer bottlenecks and boosting overall throughput. The 16 GB VRAM versus 12 GB further supports bigger models without swapping to system memory.
Power consumption reflects usage: the RTX 4070 SUPER's 200 W TDP allows deployment in lower-power setups, while the RTX 4080 SUPER's 320 W sustains peak performance for intensive sessions.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 4070 SUPER
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 4070 Ti 12GB VRAM | 12GB | 6 vCPU 30GB RAM | 🌍global | $0.50/GPU/hr |
RTX 4080 SUPER
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
RunPod | NVIDIA GeForce RTX 4080 SUPER 16GB VRAM | 16GB | 6 vCPU 35GB RAM | 🌍global | $0.50/GPU/hr | |||
RunPod | NVIDIA GeForce RTX 4080 16GB VRAM | 16GB | 6 vCPU 35GB RAM | 🌍global | $0.50/GPU/hr |
When to Choose the RTX 4070 SUPER
The RTX 4070 SUPER excels in power-constrained or cost-sensitive environments. Its 200 W TDP draws 37.5 percent less power than the RTX 4080 SUPER's 320 W, suiting small-scale clusters or edge deployments. Workloads under 12 GB VRAM and 29.1 TFLOPS suffice for efficient inference or fine-tuning of mid-sized models.
Without current cloud offers, it appeals where on-premises hardware or future pricing favors efficiency over raw speed.
When to Choose the RTX 4080 SUPER
Opt for the RTX 4080 SUPER in performance-critical applications. The 48.7 TFLOPS FP16/FP32 and 717 GB/s bandwidth handle demanding training runs 67 percent faster than the RTX 4070 SUPER's 29.1 TFLOPS and 504 GB/s. Its 16 GB VRAM accommodates larger datasets and models.
Cloud availability from $0.17 per hour positions it for scalable, on-demand use across three providers.
Use Cases
The RTX 4080 SUPER's 16 GB VRAM and 48.7 TFLOPS support larger LLMs during training, avoiding out-of-memory errors common with the RTX 4070 SUPER's 12 GB limit.
Higher 717 GB/s bandwidth on the RTX 4080 SUPER sustains larger batch sizes for low-latency inference, outperforming the RTX 4070 SUPER's 504 GB/s.
Fine-tuning mid-sized models fits within the RTX 4070 SUPER's 12 GB VRAM and 29.1 TFLOPS, but the RTX 4080 SUPER's 16 GB accelerates larger parameter sets.
Stable Diffusion workflows rarely exceed 12 GB VRAM, making the RTX 4070 SUPER's 200 W TDP and 29.1 TFLOPS sufficient for efficient image generation.
The RTX 4080 SUPER's 48.7 TFLOPS FP32 handles compute-intensive simulations faster than the RTX 4070 SUPER's 29.1 TFLOPS.
Frequently Asked Questions
What is the VRAM difference between RTX 4070 SUPER and RTX 4080 SUPER?▾
The RTX 4070 SUPER has 12 GB GDDR6X VRAM, while the RTX 4080 SUPER provides 16 GB GDDR6X. This 4 GB gap allows the RTX 4080 SUPER to load larger AI models without issues. Memory bandwidth also differs: 504 GB/s versus 717 GB/s.
Which has better performance for AI training: RTX 4070 SUPER or RTX 4080 SUPER?▾
The RTX 4080 SUPER leads with 48.7 TFLOPS in FP16 and FP32, 67 percent above the RTX 4070 SUPER's 29.1 TFLOPS. This results in faster training epochs for deep learning tasks. Higher bandwidth supports bigger batches.
RTX 4070 SUPER vs RTX 4080 SUPER power consumption?▾
The RTX 4070 SUPER TDP is 200 W, lower than the RTX 4080 SUPER's 320 W. Lower power suits constrained setups but limits peak sustained performance. Both use PCIe form factors.
Is there cloud pricing for these GPUs?▾
No live offers exist for the RTX 4070 SUPER currently. The RTX 4080 SUPER starts at $0.17 per hour, averaging $0.32 per hour across three providers. Check gpuperhour.com for updates.
RTX 4080 SUPER worth it over RTX 4070 SUPER for inference?▾
Yes for high-throughput inference: 48.7 TFLOPS and 717 GB/s bandwidth outperform 29.1 TFLOPS and 504 GB/s. For light loads, the RTX 4070 SUPER suffices with 12 GB VRAM.
Same architecture for both GPUs?▾
Both RTX 4070 SUPER and RTX 4080 SUPER use Ada Lovelace architecture. FP16 equals FP32 at 29.1 TFLOPS for 4070 SUPER and 48.7 TFLOPS for 4080 SUPER, optimizing tensor operations.
Which is cheaper to rent, the RTX 4070 or the RTX 4080?▾
Cloud rental prices for both the RTX 4070 and RTX 4080 vary by provider, configuration, and availability. This page shows live pricing from 25+ providers updated every 60 seconds. Scroll to the Live Cloud Pricing section to compare current rates.
How much VRAM does the RTX 4070 have compared to the RTX 4080?▾
The RTX 4070 has 12 GB of GDDR6X memory. The RTX 4080 has 16 GB of GDDR6X memory.
Can I find RTX 4070 and RTX 4080 GPUs available to rent right now?▾
Yes. This page shows real-time availability across 25+ cloud GPU providers. The Live Cloud Pricing section displays only in-stock offers with current pricing.
What is the main difference between the RTX 4070 and the RTX 4080?▾
The RTX 4070 uses the Ada Lovelace architecture (2023) while the RTX 4080 uses Ada Lovelace (2022). The RTX 4080 delivers 1.7x the FP16 throughput and 1.4x the memory bandwidth of the RTX 4070.